Overview

Population Characteristics

  • This dataset include 50 confirmed cases admitted from 2021-12-06 to 2025-10-08.

  • 54% women and 8% children ≤5 years.

  • 31 confirmed deaths reported for an average CFR of 62%.

Sampling

Cases Description

Patient Outcomes by Admission Delay

  • Deceased patients (n=31) had a median admission delay of 5 days (IQR range 2.25-8)
  • Recovered patients (n=50) had a median admission delay of 4 days (IQR range 1-4)

Ct kinetics

Cases and CFR

Treatments and complications

Analyses

Approach

flow ImmuneMod Immune modulation DelDirect Deleterious direct effect of virus ImmuneMod->DelDirect +/- ViralLoad Viral load ViralLoad->DelDirect + OrganFail Organ failure DelDirect->OrganFail + Death Death OrganFail->Death + PreExist Pre-existing comorbidity PreExist->OrganFail + Age Age Age->PreExist +/- Sex Sex Sex->PreExist DelayedPres Delayed presentation Sex->DelayedPres Nutrition Nutrition Nutrition->PreExist + DelayedPres->ViralLoad + Vaccination Vaccination Vaccination->ViralLoad - Antiviral Antiviral therapy Antiviral->ViralLoad - Hypoperf Hypoperfusion / shock Hypoperf->OrganFail + Dehydration Dehydration Dehydration->Hypoperf + MetElect Metabolic / electrolyte derangement Dehydration->MetElect + MetElect->OrganFail + Hypoxa Hypoxaemia Hypoxa->OrganFail + Anemia Anaemia Anemia->Hypoxa + SecInf Secondary infection SecInf->OrganFail + SecInf->Hypoxa + Bleeding Bleeding Bleeding->Anemia + ORS ORS ORS->Dehydration - IVfluid IV fluid IVfluid->Dehydration - IVfluid->MetElect - Diarrhoea Diarrhoea Diarrhoea->Dehydration +
workflow A 1. Data cleaning and wrangling B 2. Univariate model screening • Identify sparse variables • Exclude predictors causing quasi-complete separation A->B C 3. Collinearity assessment • Variance Inflation Factor (VIF) • GVIF_scaled ≤ 1.68 B->C D 4. LASSO regression • Shrinks weak predictors • Retains strongest associations C->D E 5. Multivariable logistic regression • Include LASSO-selected predictors D->E F OR from multivariable model E->F G Adjusted RR (Poisson) E->G H Raw RR for binary predictors E->H

Ct threshold to predict participant outcome

  • ROC analyses were performed to determine the optimal Ct threshold to predict participant outcome.
  • With an area under the curve (AUC) of 0.9, ROC analyses evaluated the optimal Ct threshold cut-off at 19 for predicting patients outcome (sensitivity 79%, specificity 77%).

Logistic Regression of Factors Associated with Death and Complications

Final LASSO-Selected Logistic Regression: EVD Outcome
Multivariable model including LASSO-selected predictors
Characteristic N Event N OR 95% CI p-value Significance1 Direction Unadjusted RR2 Adjusted Risk Ratio (95% CI)3
Douleurs Articulaires 36 19 19.1 0.75, 2,271 0.12 ⬆ 3.03 1.49 (0.68-3.27)
Ct at admission 36 19 0.58 0.33, 0.80 0.012 * ⬇
0.87 (0.79-0.96)
Deshydratation 36 19 0.06 0.00, 1.57 0.16 ⬇ 0.36 0.79 (0.37-1.66)
Usage d'antibiotique 36 19 1.68 0.05, 173 0.78 ⬆ 0.42 0.95 (0.54-1.66)
Difficultes respiratoires/essoufflement 36 19 0.89 0.02, 41.6 0.95 ⬇ 2.22 0.97 (0.57-1.66)
Hématémèse 36 19 8.38 0.09, 22,492 0.46 ⬆ 2.18 1.26 (0.67-2.38)
Abbreviations: CI = Confidence Interval, OR = Odds Ratio, NA
1 Odds ratios (OR) obtained by exponentiating the logistic regression coefficients (β). OR > 1 indicates increased odds of the outcome; OR < 1 indicates decreased odds.
2 Raw risk ratios (RR) were calculated as the ratio of the risk of death among participants with the condition (Yes) versus without the condition (No).
3 Adjusted risk ratios (RR) obtained from Poisson regression with robust standard errors. RR > 1 indicates increased risk; RR < 1 indicates decreased risk.
  • For each 1 Ct increase at admission, the odds of death decreased by 42% (OR 0.58, 95% CI 0.33–0.8) and the risk of death decreased by 13% (RR 0.87).

Survival Analyses

  • We used a Weibull proportional hazards model to estimate survival probabilities over time.

  • Forest plot showing relative effects of covariates on survival time estimated from a Weibull proportional hazards model. HR > 1 indicates shorter survival (faster occurrence of the event), HR < 1 indicates longer survival. Error bars represent 95% confidence intervals.
  • For example, patients with higher Ct values (>19) showed longer survival compared to those with Ct ≤19 (p value=0.0049)
  • For example, patients < age of 5 showed short survival compared to those aged 18-49 (p value=0.0083)

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